Demand Planning: 10 Essential Steps for Accurate Forecasting
By Kevin Hsu - Jan 19, 2017
Difficulty ensues when you are attempting to forecast demand and revenues for new variants of existing products. However, demand planning for radically innovative products in emerging new categories is a completely different (far more challenging) affair. Without past results and trends to base your predictions on, and a high level of uncertainty about the validity of the demand that the marketing team suggested during the final round of R&D funding, demand planning can be excruciatingly difficult.
The keys to success when it comes to demand planning are collaboration, utilizing all the quantitative and qualitative data available, and implementing a forecasting model that can quickly and easily be updated to generate detailed forecasts for all users across the business.
Here are 10 steps for new product forecasting, all of them are tried and tested practices that other businesses have found to be the best approach to new product forecasting.
Step 1: Form a core group
The first step to successful new product forecasting is to create a team of people from a variety of relevant departments (marketing, sales, operations, relevant technical departments) who can oversee and be responsible for developing and managing the reforecasting process through the launch period until demand planning becomes more predictable.
Step 2: Analyze and agree upon a set of assumptions
Using market research, market testing, and buyer surveys, your core group should then set about collectively reviewing all the accessible data (both qualitative and quantitative). Using the data, the core group must then identify and agree upon a set of assumptions, which can then be the launching-pad for forming an initial forecasting model and beginning demand planning. The core group should aim to analyze and agree upon assumptions including:
- Number of consumers in the target market
- Proportion of consumers in the target market who are expected to buy the product
- The anticipated timing of their purchase
- Patterns of repeat purchasing and replacement purchasing
The main point here is to allow the core group to use their collective expertise and judgement when analyzing and agreeing upon a set of assumptions.
Step 3: Create granular models
To ensure you are producing the most-accurate demand planning possible, your core group needs to create a forecasting model that is adequately granular enough to demonstrate when and how varying segments of the target market in different locations may purchase your product and for what price. This is especially important for radically innovative products in emerging new categories, as some consumers may wait up all-night to be the first ones to test the product out, whereas others may wait until subsequent versions are released with fixed bugs and a lower price.
Step 4: Generate responsive time periods
The sales that occur in the first few days and weeks of a new product’s life are decidedly significant. These initial days and weeks need to be meticulously monitored to help continually evolve the core group’s demand planning. While your sales team may only be interested in monthly data, at least for the first quarter commit to producing comprehensive daily forecasts.
Step 5: Produce a range of demand planning forecasts
By this point, your core group should have a detailed set of assumptions, an initial, granular forecasting model that can generate responsive time periods. The next step is to take these initial stages and to produce a broader range of demand planning forecasts. As long as you have a demand planning modelling solution that can be quickly recalculated in real-time, this step should be easy. Your range of demand planning forecasts will vary based on your specific product, but be sure to run through a number of iterations, and change a variety of assumptions and probabilities to generate a range of forecasts.
Step 6: Prepare models that preclude delays
One of the fully integrated forecasting models that needs to be created is one that will preclude delays and shorten the renewal cycle. Any firm’s demand planning needs to have a forecasting model that compares existing stock levels across locations and then automatically generates a detailed replenishment report for each one will prevent stock outs from occurring in the most uncertain period immediately after launch, as well as into the future.
Step 7: Utilize a variety of demand forecasting methods
While modelling based on purchasing intentions is an essential primary step, there are other methods that can be utilized for essential demand forecasting. While different methodologies work for different sectors, all firms can take away the fact that combining different demand forecasting techniques helps to bring you the most accurate results.
Step 8: Continuously give your demand forecast a reality-check
As more quantitative and qualitative data becomes available, continuously check the demand forecast of your sales against your actual sales and the sales of competitors. This exercise ensures that the demand forecast your core group is working with continues to be grounded in reality. If you are introducing a revolutionary product in an emerging market, this step should also include an assessment of how your firm’s market share may evolve as other competitors enter the space.
Step 9: Reforecast again and again and again
I suggest that you reforecast daily, especially in the early days of launching. These forecasts should include the results of diligently monitoring sales and qualitative feedback (such as product reviews, media mentions, customer feedback). As throughout the previous 8 steps, the members of the core group should analyze and agree on how assumptions in the model may need to change as a result.
Step 10: Have a contingency plan
After all is said and done, it is still essential that you have a realistic contingency plan. An increasingly large percentage of new businesses and fresh products fail and it is crucial that you know when it is time to cut your losses. Your core group needs to analyze and agree on what level constitutes “failure” for your product, well before your launch date.
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